Telegram RegisterThe public register of Telegram

Channel

Карьера и личный бренд врача | MD.school

@doc_kharchenko

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

7,567subscribers

-11 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001594676414
TypeChannel
Username@doc_kharchenko
DescriptionЗдесь всё о карьере врача От создателей онлайн университета доказательной медицины MD.School, выдающий дипломы гос образца и баллы НМО: https://goo.su/ASgF9o Никогда ещё обучение не было таким увлекательным🔥 10к+выпускников
CreatedBetween 1 August 2021 and 31 January 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live10 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 10 August 2026
On Telegramt.me/doc_kharchenko

Topic

Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear word for word on 2 other registered channels. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@doc_kharchenko/2366 · this entry17 Feb 2026, 13:12 UTC@mdschool_kardio/25617 Feb 2026, 13:12 UTC1.00under a minute
@doc_kharchenko/2371 · this entry27 Feb 2026, 09:39 UTC@mdschool_kardio/26127 Feb 2026, 09:40 UTC1.00under a minute
@mdschool_kardio/26918 Mar 2026, 14:32 UTC@doc_kharchenko/2378 · this entry18 Mar 2026, 14:32 UTC1.00under a minute
@doc_kharchenko/2388 · this entry28 May 2026, 13:00 UTC@mdschool_kardio/27228 May 2026, 13:03 UTC1.003 minutes
@doc_kharchenko/2389 · this entry1 Jun 2026, 15:12 UTC@mdschool_kardio/2732 Jun 2026, 12:00 UTC1.0021 hours
@mdschool_kardio/27724 Jul 2026, 16:02 UTC@doc_kharchenko/2403 · this entry24 Jul 2026, 16:05 UTC1.002 minutes
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@mdschool_kardio11 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (92)
@MDSchool_ophthalmology6 (6/6 hand-verifiable sample passed)1.002 minutesthis entry (51)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 1 of the 3 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 13 comparable posts for this entry, running 17 February 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Across the whole group of 3, the earliest publisher we hold is @doc_kharchenko — which is this entry. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_source, last confirmed 8 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Also posting the same content

This channel’s posts match, word for word or near enough, posts on 2 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.

Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

7,5677,5787,572.57 August 2026 — 7,578 subscribers7 August 2026 — 7,578 subscribers7 August 2026 — 7,576 subscribers10 August 2026 — 7,567 subscribers7 August 202610 August 2026
4 measurements spanning 3 days, net -11. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 7,565–7,580 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Aug 2026, 17:557,567-9
7 Aug 2026, 21:377,576-2
7 Aug 2026, 08:007,578no change
7 Aug 2026, 07:557,578first reading

Engagement

13 posts held, back to 17 February 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 11 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
3.03%
avg views ÷ 7,567 subscribers
Avg views / post
230
4 posts measured
Reaction rate
1.35%
reactions ÷ views · ER floor
Posts in window
4
of 13 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 1 of 4 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 7 August 2026
Posts held13 (17 February 20267 August 2026)
Views total918
Reactions total4
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 17:20 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Photos
668
Videos
85
Links
413

Lifetime counters from Telegram’s own channel header, read 12 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Video runtime
4m 13s
Average length
2m 07s

Measured directly from 2 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Reaction mix

11 reactions across 5 posts, in 4 distinct kinds. The most used accounts for 54.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
654.5%
👍327.3%
🙏19.09%
🤔19.09%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 5 of the 13 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 11reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 13 most recent posts we hold, published 17 February 2026 to 7 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

7 Aug 2026, 09:43 UTC142 viewsread 12 August 2026
Photo

Не покупайте курсы за полную стоимость 👀 если вы студент или ординатор Пока у вас есть этот статус, MD.school оплачивает 50% обучения. MD.school — онлайн-университет доказательной медицины для врачей. По гранту вы можете выбрать любой курс и оплатить только половину его стоимости. Что можно выбрать: • Клинические направления Гинекология, неврология, эндокринология, педиатрия, офтальмология, онкология, хирургия •

30 Jul 2026, 08:05 UTC240 viewsread 12 August 2026
Photo

Как разобрать новые клинреки за минуты и быстро собрать по ним лекцию? Разбираем реальный кейс 🩺 Чтение новых клинических рекомендаций — это всегда часы кропотливой работы. А если руководство просит еще и срочно подготовить по ним выжимку или обучение для коллег? В чате нашего курса ученица Айгуль поделилась видео-отзывом о том, как нейросети превращают эту рутину в быстрый, точный и управляемый процесс. Мы разобра

27 Jul 2026, 11:23 UTC240 viewsread 12 August 2026
Photo

Не надо работать на износ, чтобы делать больше. Достаточно одного помощника. Один день врача — это десятки задач, кроме приёма пациентов. Помимо консультаций и заполнения меддокументации, врач каждый день сталкивается с задачами, которые съедают часы: ● Оформить справку в комиссию или для МСЭ ● Ответить пациенту на жалобу или составить объяснительную ● Сделать слайды и доклад для конференции ● Собрать материал

24 Jul 2026, 16:05 UTC296 views4 reactionsread 12 August 2026
Video

Как врач готовит презентацию для международной конференции с помощью нейросетей меньше, чем за час. Кейс ученицы курса «Нейросети в работе врача» — Юлии Топаловой, гастроэнтеролога и гепатолога из Санкт-Петербурга. За 4 недели обучения Юлия полностью перестроила подход к созданию медицинских презентаций. Раньше — долгий поиск статей, ручная структура, оформление. Сейчас — работа заняла менее часа благодаря ChatGPT

👍3🤔1

1 Jun 2026, 15:12 UTC906 views3 reactionsread 12 August 2026
Photo

Если у вас есть дети — кажется, вам будет особенно интересно 💚 Сейчас открыты 7 дней бесплатного доступа к Ай Болит Kids — можете протестировать и как врач, и как родитель. Ай Болит Kids — AI-педиатра для родителей детей 0–7 лет. Мы сделали его, потому что знаем: даже врачи, когда болеет собственный ребёнок, остаются прежде всего родителями. И так же сталкиваются с вопросами про температуру, сон, питание, анализы,

3

28 May 2026, 13:00 UTC743 views1 reactionsread 12 August 2026
Photo

✍️ Не все врачебные курсы одинаково полезны.. Поэтому многие приходят в MD.school после: — хаотичных вебинаров — устаревших подходов — лекций без практики, готовых алгоритмов — обучения, которое не помогает на реальном приёме. Сейчас для новых учеников: –25% на первый курс MD.school 🤍 В MD.school: — доказательная медицина — практические алгоритмы для реальных клинических ситуаций — обучение, которое применяется на

🙏1

13 May 2026, 17:27 UTC686 viewsread 12 August 2026
Photo

🔥Более 100 сохранений у этого поста! 🔥 Мы собрали все самые полезные ИИ-запросы для врачей в единый дайджест. Внутри находятся готовые шаблоны для первичного осмотра, поиска научных статей и ведения медицинского блога. 📎Убедитесь, что вы добавили этот полезный список в свои закладки. Забрать дайджест промптов

28 Apr 2026, 07:53 UTC878 viewsread 12 August 2026
Photo

Бесплодие «омолаживается». А алгоритмы — усложняются 🔍 Пациенты приходят уже с анализами, диагнозами из интернета и ожиданием «быстрого результата». И здесь легко ошибиться: ❌назначить лишнее, ❌пропустить важное, ❌неверно выстроить маршрут. Сейчас можно закрыть эту зону системно⬇️ «Амбулаторная гинекология» + закрытый эфир в подарок С 28 по 30 апреля включительно при покупке курса вы бесплатно получаете лекцию:

18 Mar 2026, 14:32 UTC996 viewsread 12 August 2026

Коротко о главном в научной повестке Канал для тех, кто хочет успевать следить за тем, что реально происходит в академической среде, но не готов читать бесконечные ленты новостей. Здесь выборочно, но метко: — Разборы диссертаций, которые уже успели получить ученую степень (и вопросов к ним больше, чем ответов); — Навигация по «Белым спискам» и требованиям ВАК — без паники, но с пониманием подводных камней; — Истори

13 Mar 2026, 08:56 UTC989 views2 reactionsread 12 August 2026
Photo

🎁 Дарим гайд с алгоритмами работы для быстрого поиска и проверки информации Скачивайте бесплатно еще много полезной информации для врачей в канале: ✔️ По работе с научными публикациями: - как написать научную статью и успешно ее опубликовать - как правильно ответить рецензенту - поиск темы и обзор литературы с помощью нейросетей ✔️ Использование нейросетей во врачебной практике + готовые запросы: - нейросети для и

2

27 Feb 2026, 09:39 UTC922 viewsread 12 August 2026
Photo

8 источников, где врач может проверить реальную доказательную эффективность препарата Где вы проверяете доказательную базу препарата, который планируете назначить? Госреестр? PubMed? Cochrane? А если данные противоречивые или исследования «на грани»? В канале MD.school по рентгенологии опубликовали подборку из 8 источников, где врач может проверить реальную доказательную эффективность препарата: ✅ почему регистраци

19 Feb 2026, 08:18 UTC845 views1 reactionsread 12 August 2026
Photo

🔥 Отдаем 70+ учебных пособий для врача! Все необходимые гайды, чек-листы и пошаговые алгоритмы ждут учеников курса «Профессия нутрициолог: доказательный подход к питанию»! То, что можно применять с первого дня обучения и то, что достается ученикам БЕСПЛАТНО 🔥 Мы собрали для вас уникальную библиотеку учебных материалов, которая станет вашей настольной книгой и незаменимым помощником в работе: ✔️Подробные гайды и л

1

Showing the 12 most recent of 13 posts we hold for @doc_kharchenko. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Mentions

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 10 August 2026 — this entry's latest reading, not the date you are reading this.

“Карьера и личный бренд врача | MD.school” (@doc_kharchenko), 7,567 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/doc_kharchenko.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.